The $17 Billion Lesson: How to Think Like Ray Dalio

Tony Robbins (left) and Ray Dalio. (Inc.)

Part of the “Entrepreneurship Unplugged” Blog Series: Blog 6

I recently finished reading Ray Dalio’s book “Principles.” At an estimated net worth of more than $17B, Dalio is one of the most successful hedge fund managers in the world, starting out in 1975 from his own home. Bridgewater Associates has since grown to be one of the five largest private companies in the United States.

As with most successful people, Dalio has learned more from his mistakes than his successes. His most painful learning experience occurred in 1982, when Mexico defaulted on his loans. While having correctly predicted the credit crisis, the markets went up rather than down, followed by an 18-year long bull market. Despite having been right, this mistake almost bankrupted the company and Dalio was forced to let everyone, except himself, go. In hindsight, he notes that when leading up to this monumental failure, his own arrogance was the best thing that could have happened to him. Watch his great TedTalk for the whole story, here.

Instead of going back to a comfortable Wall Street job in the aftermath of 1982, Dalio chose to learn from his mistakes and ensure Bridgewater got back on its feet. His book “Principles” captures the essence of what has been driving Bridgewater and, by extension, his continued success for the past 30+ years.

“If you’re not failing, you’re not pushing your limits, and if you’re not pushing your limits, you’re not maximizing your potential”

SYSTEMATIZING YOUR DECISIONS

What resonated most with me from “Principles” is the proposed systemized approach to decision-making. Essentially, a way of turning all your learning experiences, good or bad, into principles and eventually computer algorithms. Imagine that every time you make a decision, there is a little person in your ear, equipped with a powerful computer, that tells you what to do based on your past track record.

The important distinction is that augmented decision-making isn’t just about random success! It’s about success that is the result of continuous learning and a systematized approach.

So I decided to put Dalio’s “Principles” to the test for all of us entrepreneurs building startups in every corner of the world. I wanted to find an answer to the burning question that’s been on my mind ever since I finished reading his book:

Can Dalio’s systems approach be applied to startups?

In order to better understand how “Principles” can lead to success, here’s how Dalio implemented his principles at Bridgewater. There are two key areas:

1. Investment AND 2. Company Decisions

MAKING THE RIGHT INVESTMENT: A Lesson from the Best-Of-The-Best

The majority of Bridgewater’s success is dependent on their investment decisions day-in and day-out. Their investments, in return, are a result of the basics: HOW to invest, WHEN to invest, and WHAT to invest in. While “basics,” these three questions (or principles) can be extremely difficult to predict and answer. So Dalio, as well as other senior investment professionals, turned their principles into computer algorithms. These algorithms don’t replace daily decisions, they augment them.

Knowing that Bridgewater’s investment success is the core driver of their overall success and rise to fame, I asked myself if it’s possible to transfer these learning experiences to a startup. Just imagine the benefits of an algorithm-driven decision support system that helps entrepreneurs successfully navigate the daily challenges of building a company as a first-time founder, or even as a serial entrepreneur!

“Principles are fundamental truths that serve as the foundations for behavior that gets you what you want out of life. They can be applied again and again in similar situations to help you achieve your goals.”

The more I thought about this compelling idea, the more I came to the realization that Dalio’s Bridgewater approach is unique to the finance industry. Stock market predictions are based on vast amounts of data, including economic, financial, and historical data sets. Stock market data goes back almost 200 years! In order to become a great investor, a large portion of your success is based on your ability to understand markets, as well as develop algorithms and models to better predict stock market behavior.

So, why doesn’t this approach work for startups? Here are just a few key questions (or obstacles) that I came up with when trying to apply investment approaches to the startup world:

1. How many publicly accessible, or even paid, structured data sets exist that would help entrepreneurs make better business decisions?
2. How much can we really learn from the past if we consider the innovative, and therefore unproven, nature of most business models?
3. How many entrepreneurs innovate and create new industry or market segments, as opposed to building businesses in existing ones?

This isn’t to say that I dislike augmented decision-making. What these questions make clear is that there’s no logical or algorithms-based decision-making approach for startups that is comparable to a hedge fund. Simply put, unlike with stock markets, there’s not enough structured or available data on the startup world to build algorithms and succeed in the same way Dalio has with Bridgewater.

However, I’m not writing off Dalio’s ideas of applying principles to start-ups completely.

COMPANY DECISIONS: How To Make The Right Ones

The first part of Dalio’s approach focused on investment decisions. But there’s a second part, about applying “Principles” to your company, which includes human resource decisions, daily interactions with colleagues, when to let people go, and much more.

“The pain of problems is a call to find solutions rather than a reason for unhappiness and inaction, so it’s silly, pointless, and harmful to be upset at the problems and choices that come at you.”

Even though it’s difficult to quantify human behavior in the same way as stock markets, Dalio relies heavily on psychometric testing for his employees. Think of it as a personality test that helps you understand the strengths and weaknesses of each individual; at Bridgewater, they use classic tests such as the Myers-Briggs. But that’s not all!

Each employee also gets a virtual baseball card that summarizes results from tests and reviews evaluated by algorithms. The “baseball card” data is used to match people with projects based on their skills. Let’s assume a project manager is looking for a creative person to join a project. By easily searching in their internal database for someone that matches the needed or required skill set, they’ve got the perfect fit.

This idea is not just compelling, it’s feasible. Rather than relying on past or historical data like with the stock markets, you can collect your own personality data before and after you have hired someone. How many startups do YOU know who test employees’ personality, one way or another? We all know how critical first hires are. The wrong hire can literally break your company. So why wouldn’t we base our hiring decisions more heavily on data rather than just our gut? It’s not only for the sake of finding better people, either. Algorithms can also to spark productivity through improved matching mechanisms within startup teams.

I hope this thought experiment has made you think of how to best apply Dalio’s “Principles” to your startup. While this blog focused on the principles of investment and company decisions, we all know those aren’t the only two things that form the foundation of any company.

According to Dalio, a company consists of two things: people 👫 and culture 🌍

There are many ways to take Dalio’s hard-learned lessons and apply them to any company, from the newest startup to one of the world’s biggest hedge funds. If you haven’t already read “Principles” and want a quick understanding of the key takeaways, spend a few minutes watching this great video. You’ll learn more about the culture of Dalio’s idea meritocracy, comprised of greats ideas that include radical transparency, thoughtful disagreement, and fair and appropriate ways to get past disagreements.

I’m really looking forward to your comments, likes and other ways of engagement. 😀🙏

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